Whole-brain Structural Networks Research Articles

White matter network underlying semantic processing: evidence from stroke patients.

The hub-and-spoke theory of semantic representation fractionates the neural underpinning of semantic knowledge into two essential components: the sensorimotor modality-specific regions and a crucially important semantic hub region. Our previous study in patients with semantic dementia has found that the hub region is located in the left fusiform gyrus. However, because this region is located within the brain damage in patients with semantic dementia, it is not clear whether the semantic deficit is caused by structural damage to the hub region itself or by its disconnection from other brain regions. Stroke patients do not have any damage to the left fusiform gyrus, but exhibit amodal and modality-specific deficits in semantic processing. Therefore, in this study, we validated the semantic hub region from a brain network perspective in 79 stroke patients and explored the white matter connections associated with it. First, we collected data of diffusion-weighted imaging and behavioural performance on general semantic tasks and modality-specific semantic tasks (assessing object knowledge on form, colour, motion, sound, manipulation and function). We then used correlation and regression analyses to examine the association between the nodal degree values of brain regions in the whole-brain structural network and general semantic performance in the stroke patients. The results revealed that the connectivity of the left fusiform gyrus significantly predicted general semantic performance, indicating that this region is the semantic hub. To identify the semantic-relevant connections of the semantic hub, we then correlated the white matter integrity values of each tract connected to the left fusiform gyrus separately with performance on general and modality-specific semantic processing. We found that the hub region accomplished general semantic processing through white matter connections with the left superior temporal pole, middle temporal gyrus, inferior temporal gyrus and hippocampus. The connectivity between the hub region and the left hippocampus, superior temporal pole, middle temporal gyrus, inferior temporal gyrus and parahippocampal gyrus was differentially involved in object form, colour, motion, sound, manipulation and function processing. After statistically removing the effects of potential confounding variables (i.e. whole-brain lesion volume, lesion volume of regions of interest and performance on non-semantic control tasks), the observed effects remained significant. Together, our findings support the role of the left fusiform gyrus as a semantic hub region in stroke patients and reveal its crucial connectivity in the network. This study provides new insights and evidence for the neuroanatomical organization of semantic memory in the human brain.

Abnormal wiring of the structural connectome in adults with ADHD.

Current knowledge of white matter changes in large-scale brain networks in adult attention-deficit/hyperactivity disorder (ADHD) is scarce. We collected diffusion-weighted magnetic resonance imaging data in 40 adults with ADHD and 36 neurotypical controls and used constrained spherical deconvolution-based tractography to reconstruct whole-brain structural connectivity networks. We used network-based statistic (NBS) and graph theoretical analysis to investigate differences in these networks between the ADHD and control groups, as well as associations between structural connectivity and ADHD symptoms assessed with the Adult ADHD Self-Report Scale or performance in the Conners Continuous Performance Test 2 (CPT-2). NBS revealed decreased connectivity in the ADHD group compared to the neurotypical controls in widespread unilateral networks, which included subcortical and corticocortical structures and encompassed dorsal and ventral attention networks and visual and somatomotor systems. Furthermore, hypoconnectivity in a predominantly left-frontal network was associated with higher amount of commission errors in CPT-2. Graph theoretical analysis did not reveal topological differences between the groups or associations between topological properties and ADHD symptoms or task performance. Our results suggest that abnormal structural wiring of the brain in adult ADHD is manifested as widespread intrahemispheric hypoconnectivity in networks previously associated with ADHD in functional neuroimaging studies.

Impaired rich-club connectivity in childhood absence epilepsy.

Childhood absence epilepsy (CAE) is a well-known pediatric epilepsy syndrome. Recent evidence has shown the presence of a disrupted structural brain network in CAE. However, little is known about the rich-club topology. This study aimed to explore the rich-club alterations in CAE and their association with clinical characteristics. Diffusion tensor imaging (DTI) datasets were acquired in a sample of 30 CAE patients and 31 healthy controls. A structural network was derived from DTI data for each participant using probabilistic tractography. Then, the rich-club organization was examined, and the network connections were divided into rich-club connections, feeder connections, and local connections. Our results confirmed a less dense whole-brain structural network in CAE with lower network strength and global efficiency. In addition, the optimal organization of small-worldness was also damaged. A small number of highly connected and central brain regions were identified to form the rich-club organization in both patients and controls. However, patients exhibited a significantly reduced rich-club connectivity, while the other class of feeder and local connections was relatively spared. Moreover, the lower levels of rich-club connectivity strength were statistically correlated with disease duration. Our reports suggest that CAE is characterized by abnormal connectivity concentrated to rich-club organizations and might contribute to understanding the pathophysiological mechanism of CAE.

Differences in structural connectivity between diabetic and psychological erectile dysfunction revealed by network-based statistic: A diffusion tensor imaging study.

IntroductionType 2 diabetes mellitus (T2DM) has been found to be associated with abnormalities of the central and peripheral vascular nervous system, which were considered to be involved in the development of cognitive impairments and erectile dysfunction (ED). In addition, altered brain function and structure were identified in patients with ED, especially psychological ED (pED). However, the similarities and the differences of the central neural mechanisms underlying pED and T2DM with ED (DM-ED) remained unclear.MethodsDiffusion tensor imaging data were acquired from 30 T2DM, 32 ED, and 31 DM-ED patients and 47 healthy controls (HCs). Then, whole-brain structural networks were constructed, which were mapped by connectivity matrices (90 × 90) representing the white matter between 90 brain regions parcellated by the anatomical automatic labeling template. Finally, the method of network-based statistic (NBS) was applied to assess the group differences of the structural connectivity.ResultsOur NBS analysis demonstrated three subnetworks with reduced structural connectivity in DM, pED, and DM-ED patients when compared to HCs, which were predominantly located in the prefrontal and subcortical areas. Compared with DM patients, DM-ED patients had an impaired subnetwork with increased structural connectivity, which were primarily located in the parietal regions. Compared with pED patients, an altered subnetwork with increased structural connectivity was identified in DM-ED patients, which were mainly located in the prefrontal and cingulate areas.ConclusionThese findings highlighted that the reduced structural connections in the prefrontal and subcortical areas were similar mechanisms to those associated with pED and DM-ED. However, different connectivity patterns were found between pED and DM-ED, and the increased connectivity in the frontal–parietal network might be due to the compensation mechanisms that were devoted to improving erectile function.

Structural network alterations in focal and generalized epilepsy assessed in a worldwide ENIGMA study follow axes of epilepsy risk gene expression

Epilepsy is associated with genetic risk factors and cortico-subcortical network alterations, but associations between neurobiological mechanisms and macroscale connectomics remain unclear. This multisite ENIGMA-Epilepsy study examined whole-brain structural covariance networks in patients with epilepsy and related findings to postmortem epilepsy risk gene expression patterns. Brain network analysis included 578 adults with temporal lobe epilepsy (TLE), 288 adults with idiopathic generalized epilepsy (IGE), and 1328 healthy controls from 18 centres worldwide. Graph theoretical analysis of structural covariance networks revealed increased clustering and path length in orbitofrontal and temporal regions in TLE, suggesting a shift towards network regularization. Conversely, people with IGE showed decreased clustering and path length in fronto-temporo-parietal cortices, indicating a random network configuration. Syndrome-specific topological alterations reflected expression patterns of risk genes for hippocampal sclerosis in TLE and for generalized epilepsy in IGE. These imaging-transcriptomic signatures could potentially guide diagnosis or tailor therapeutic approaches to specific epilepsy syndromes.

Longitudinal Changes in Structural Connectivity in Young People at High Genetic Risk for Bipolar Disorder.

Recent studies of patients with bipolar disorder or at high genetic risk reveal structural dysconnections among key brain networks supporting cognitive and affective processes. Understanding the longitudinal trajectories of these networks across the peak age range of bipolar disorder onset could inform mechanisms of illness onset or resilience. Longitudinal diffusion-weighted MRI and phenotypic data were acquired at baseline and after 2 years in 183 individuals ages 12-30 years in two cohorts: 97 unaffected individuals with a first-degree relative with bipolar disorder (the high-risk group) and 86 individuals with no family history of mental illness (the control group). Whole-brain structural networks were derived using tractography, and longitudinal changes in these networks were studied using network-based statistics and mixed linear models. Both groups showed widespread longitudinal changes, comprising both increases and decreases in structural connectivity, consistent with a shared neurodevelopmental process. On top of these shared changes, high-risk participants showed weakening of connectivity in a network encompassing the left inferior and middle frontal areas, left striatal and thalamic structures, the left fusiform, and right parietal and occipital regions. Connections among these regions strengthened in the control group, whereas they weakened in the high-risk group, shifting toward a cohort with established bipolar disorder. There was marginal evidence for even greater network weakening in those who had their first manic or hypomanic episode before follow-up. Neurodevelopment from adolescence into early adulthood is associated with a substantial reorganization of structural brain networks. Differences in these maturational processes occur in a multisystem network in individuals at high genetic risk of bipolar disorder. This may represent a novel candidate to understand resilience and predict conversion to bipolar disorder.

The disrupted topological properties of structural networks showed recovery in ischemic stroke patients: a longitudinal design study

IntroductionStroke is one of the leading causes of substantial disability worldwide. Previous studies have shown brain functional and structural alterations in adults with stroke. However, few studies have examined the longitudinal reorganization in whole-brain structural networks in stroke.MethodsHere, we applied graph theoretical analysis to investigate the longitudinal topological organization of white matter networks in 20 ischemic stroke patients with a one-month interval between two timepoints. Two sets of clinical scores, Fugl-Meyer motor assessment (FMA) and neurological deficit scores (NDS), were assessed for all patients on the day the image data were collected.ResultsThe stroke patients exhibited significant increases in FMA scores and significant reductions in DNS between the two timepoints. All groups exhibited small-world organization (σ > 1) in the brain structural network, including a high clustering coefficient (γ > 1) and a low normalized characteristic path length (λ ≈ 1). However, compared to healthy controls, stroke patients showed significant decrease in nodal characteristics at the first timepoint, primarily in the right supplementary motor area, right middle temporal gyrus, right inferior parietal lobe, right postcentral gyrus and left posterior cingulate gyrus. Longitudinal results demonstrated that altered nodal characteristics were partially restored one month later. Additionally, significant correlations between the nodal characteristics of the right supplementary motor area and the clinical scale scores (FMA and NDS) were observed in stroke patients. Similar behavioral-neuroimaging correlations were found in the right inferior parietal lobe.ConclusionAltered topological properties may be an effect of stroke, which can be modulated during recovery. The longitudinal results and the neuroimaging-behavioral relationship may provide information for understanding brain recovery from stroke. Future studies should detect whether observed changes in structural topological properties can predict the recovery of daily cognitive function in stroke.

Altered gray matter structural covariance networks in postpartum depression: a graph theoretical analysis

BackgroundPostpartum depression (PPD) is a serious postpartum mental health problem worldwide. To date, minimal is known about the alteration of topographical organization in the brain structural covariance network of patients with PPD. This study investigates the brain structural covariance networks of patients with PPD by using graph theoretical analysis. MethodsHigh-resolution 3D T1 structural images were acquired from 21 drug-naive patients with PPD and 18 healthy postpartum women. Cortical thickness was extracted from 64 brain regions to construct the whole-brain structural covariance networks by calculating the Pearson correlation coefficients, and their topological properties (e.g., small-worldness, efficiency, and nodal centrality) were analyzed by using graph theory. Nonparametric permutation tests were further used for group comparisons of topological metrics. A node was set as a hub if its betweenness centrality (BC) was at least two standard deviations higher than the mean nodal centrality. Network-based statistic (NBS) was used to determine the connected subnetwork. ResultsThe PPD and control groups showed small-worldness of group networks, but the small-world network was more evidently in the PPD group. Moreover, the PPD group showed increased network local efficiency and almost similar network global efficiency. However, the difference of the network metrics was not significant across the range of network densities. The hub nodes of the patients with PPD were right inferior parietal lobule (BC = 13.69) and right supramarginal gyrus (BC = 13.15), whereas those for the HCs were left cuneus (BC = 14.96), right caudal anterior-cingulate cortex (BC = 15.51), and right precuneus gyrus (BC = 15.74). NBS demonstrated two disrupted subnetworks that are present in PPD: the first subnetwork with decreased internodal connections is mainly involved in the cognitive-control network and visual network, and the second subnetwork with increased internodal connections is mainly involved in the default mode network, cognitive-control network and visual network. ConclusionsThis study demonstrates the alteration of topographical organization in the brain structural covariance network of patients with PPD, providing in sight on the notion that PPD could be characterized as a systems-level disorder.

Associations between hemispheric asymmetry and schizophrenia-related risk genes in people with schizophrenia and people at a genetic high risk of schizophrenia.

Schizophrenia is considered a polygenic disorder. People with schizophrenia and those with genetic high risk of schizophrenia (GHR) have presented with similar neurodevelopmental deficits in hemispheric asymmetry. The potential associations between neurodevelopmental abnormalities and schizophrenia-related risk genes in both schizophrenia and those with GHR remains unclear. To investigate the shared and specific alternations to the structural network in people with schizophrenia and those with GHR. And to identify an association between vulnerable structural network alternation and schizophrenia-related risk genes. A total of 97 participants with schizophrenia, 79 participants with GHR and 192 healthy controls, underwent diffusion tensor imaging (DTI) scans at a single site. We used graph theory to characterise hemispheric and whole-brain structural network topological metrics. For 26 people in the schizophrenia group and 48 in the GHR group with DTI scans we also calculated their schizophrenia-related polygenic risk scores (SZ-PRSs). The correlations between alterations to the structural network and SZ-PRSs were calculated. Based on the identified genetic-neural association, bioinformatics enrichment was explored. There were significant hemispheric asymmetric deficits of nodal efficiency, global and local efficiency in the schizophrenia and GHR groups. Hemispheric asymmetric deficit of local efficiency was significantly positively correlated with SZ-PRSs in the schizophrenia and GHR groups. Bioinformatics enrichment analysis showed that these risk genes may be linked to signal transduction, neural development and neuron structure. The schizophrenia group showed a significant decrease in the whole-brain structural network. The shared asymmetric deficits in people with schizophrenia and those with GHR, and the association between anomalous asymmetry and SZ-PRSs suggested a vulnerability imaging marker regulated by schizophrenia-related risk genes. Our findings provide new insights into asymmetry regulated by risk genes and provides a better understanding of the genetic-neural pathological underpinnings of schizophrenia.

Disconnectomics of the Rich Club Impacts Motor Recovery After Stroke.

Structural brain networks possess a few hubs, which are not only highly connected to the rest of the brain but are also highly connected to each other. These hubs, which form a rich-club, play a central role in global brain organization. To investigate whether the concept of rich-club sheds new light on poststroke recovery, we applied a novel network-theoretical quantification of lesions to patients with stroke and compared the outcomes with what lesion size alone would indicate. Whole-brain structural networks of 73 patients with ischemic stroke were reconstructed using diffusion-weighted imaging data. Disconnectomes, a new type of network analyses, were constructed using only those fibers that pass through the lesion. Fugl-Meyer upper extremity scores and their changes were used to determine whether the patients show natural recovery or not. Cluster analysis revealed 3 patient clusters: small-lesion-good-recovery, midsized-lesion-poor-recovery (MLPR), and large-lesion-poor-recovery (LLPR). The small-lesion-good-recovery consisted of subjects whose lesions were small, and whose prospects for recovery were relatively good. To explain the nondifference in recovery between the MLPR and LLPR clusters despite the difference (LLPR>MLPR) in lesion volume, we defined the [Formula: see text] metric to be the sum of the entries in the disconnectome and, more importantly, the [Formula: see text] to be the sum of all entries in the disconnectome corresponding to edges with at least one node in the rich-club. Unlike lesion volume and corticospinal tract damage (MLPR<LLPR), for [Formula: see text], this relationship was reversed (MLPR>LLPR) or showed no difference for [Formula: see text]. Smaller lesions that focus on the rich-club can be just as devastating as much larger lesions that do not focus on the rich-club, pointing to the role of the rich-club as a backbone for functional communication within brain networks and for recovery from stroke.

Internet gaming disorder impacts gray matter structural covariance organization in the default mode network

IntroductionAlthough previous studies have revealed that dysfunctional brain organization is associated with internet gamingdisorder (IGD), the neuroanatomical basis that underlies IGD remains elusive. In this work, we aimed to investigate gray matter (GM) volume alterations and structural covariance patterns in relation to IGD severity. MethodsStructural magnetic resonance imaging data were acquired from two hundred and thirty young adults encompassing a wide range of IGD severity. Voxel-based morphometry (VBM) analysis was applied to examine GM volume changes associated with IGD severity. Furthermore, the organization of whole-brain structural covariance network (SCN) was analyzed using the regions identified as seeds from VBM analysis. ResultsIndividuals with greater IGD severity had increased GM volumes in the midline components of the default mode network (DMN), namely, the right medial prefrontal cortex (mPFC) and precuneus. More importantly, the SCN results revealed impaired patterns of structural covariance between the DMN-related regions and areas associated with visuospatial attention and reward craving processing as the addiction severity of IGD worsened. LimitationsOnly young Chinese adults were enrolled in our study andthe extent to which findings generalize to samples in other age groups and diverse cultures is unclear. ConclusionsThese results showed volume expansion of the DMN components and its weakened structural association with visuospatial attention and motivational craving regions with increasing IGD severity. This study deepens our understanding of the underlying neuroanatomical correlates of IGD, which may help to explain why some individuals are more vulnerable to compulsive gaming usage than others.

Aberrant Structural Network Architecture in Leber’s Hereditary Optic Neuropathy. Minimum Spanning Tree Graph Analysis Application into Diffusion 7T MRI

Examining individuals with Leber’s hereditary optic neuropathy (LHON) provides a rare opportunity to understand how changes in mitochondrial DNA and loss of vision can be related to changes in organization of the whole-brain structural network architecture. In comparison with the previous neuroimaging studies with LHON participants, which were focused mainly on analyzing changes which occur in different areas of the patient’s brain, network analysis not only makes it possible to observe single white matter fibers’ aberrations but also the whole-brain nature of these changes. The purpose of our study was to better understand whole-brain neural network changes in LHON participants and see the correlation between the clinical data and the changes. To achieve this, we examined fifteen LHON patients and seventeen age-matched healthy subjects with the usage of ultra-high filed 7T magnetic resonance imaging (MRI). Basing on the analysis on MRI diffusion tensor imaging (DTI) data, whole-brain structural neural networks were reconstructed with the use of the minimum spanning tree algorithm (MST) for every participant. Our results revealed that the structural network in LHON participants was altered at both the local and the global level. The global network structures of LHON subjects were less centralized with path-like organization and there was an imbalance in the main hub centrality. Moreover, the inspection of nodes and hubs in terms of their anatomical placement revealed that in the LHON participants the prominent hubs were located within the basal ganglia (i.e. bilateral caudate, left pallidum), which differed them from healthy controls. An analysis of the relationships between the global MST metrics and LHON participants’ clinical characteristics revealed significant correlations between the global network metrics and the duration of illness. Furthermore, the nodal parameters of the optic chiasm were significantly correlated with the duration of illness and the averaged thickness of the right retinal nerve fiber layer (RNFL). These findings clearly showed that the progression of the disease is accompanied by alterations within the brain network structure and its efficiency.

Abnormal rich club organization in end-stage renal disease patients before dialysis initiation and undergoing maintenance hemodialysis

BackgroundEnd-stage renal disease (ESRD) patients are at a substantially higher risk for developing cognitive impairment compared with the healthy population. Dialysis is an essential way to maintain the life of ESRD patients. Based on previous research, there isn’t an uncontested result whether cognition was improved or worsened during dialysis.MethodsTo explore the impact of dialysis treatment on cognitive performance, we recruited healthy controls (HCs), predialysis ESRD patients (predialysis group), and maintenance hemodialysis ESRD patients (HD group). All ESRD patients performed six blood biochemistry tests (hemoglobin, urea, cystatin C, Na+, K+, and parathyroid hormone). Neuropsychological tests were used to measure cognitive function. By using diffusion tensor imaging and graph-theory approaches, the topological organization of the whole-brain structural network was investigated. Generalized linear models (GLMs) were performed to investigate blood biochemistry predictors of the neuropsychological tests and the results of graph analyses in the HD group and predialysis group.ResultsNeuropsychological analysis showed the HD group exhibited better cognitive function than the predialysis group, but both were worse than HCs. Whole-brain graph analyses revealed that increased global efficiency and normalized shortest path length remained in the predialysis group and HD group than the HCs. Besides, a lower normalized clustering coefficient was found in the predialysis group relative to the HCs and HD group. For the GLM analysis, only the Cystatin C level was significantly associated with the average fiber length of rich club connections in the predialysis group.ConclusionsOur study revealed that dialysis had a limited effect on cognitive improvement.

Preterm birth leads to impaired rich-club organization and fronto-paralimbic/limbic structural connectivity in newborns

Prematurity disrupts brain development during a critical period of brain growth and organization and is known to be associated with an increased risk of neurodevelopmental impairments. Investigating whole-brain structural connectivity alterations accompanying preterm birth may provide a better comprehension of the neurobiological mechanisms related to the later neurocognitive deficits observed in this population.Using a connectome approach, we aimed to study the impact of prematurity on neonatal whole-brain structural network organization at term-equivalent age. In this cohort study, twenty-four very preterm infants at term-equivalent age (VPT-TEA) and fourteen full-term (FT) newborns underwent a brain MRI exam at term age, comprising T2-weighted imaging and diffusion MRI, used to reconstruct brain connectomes by applying probabilistic constrained spherical deconvolution whole-brain tractography. The topological properties of brain networks were quantified through a graph-theoretical approach. Furthermore, edge-wise connectivity strength was compared between groups.Overall, VPT-TEA infants’ brain networks evidenced increased segregation and decreased integration capacity, revealed by an increased clustering coefficient, increased modularity, increased characteristic path length, decreased global efficiency and diminished rich-club coefficient. Furthermore, in comparison to FT, VPT-TEA infants had decreased connectivity strength in various cortico-cortical, cortico-subcortical and intra-subcortical networks, the majority of them being intra-hemispheric fronto-paralimbic and fronto-limbic. Inter-hemispheric connectivity was also decreased in VPT-TEA infants, namely through connections linking to the left precuneus or left dorsal cingulate gyrus – two regions that were found to be hubs in FT but not in VPT-TEA infants. Moreover, posterior regions from Default-Mode-Network (DMN), namely precuneus and posterior cingulate gyrus, had decreased structural connectivity in VPT-TEA group.Our finding that VPT-TEA infants’ brain networks displayed increased modularity, weakened rich-club connectivity and diminished global efficiency compared to FT infants suggests a delayed transition from a local architecture, focused on short-range connections, to a more distributed architecture with efficient long-range connections in those infants. The disruption of connectivity in fronto-paralimbic/limbic and posterior DMN regions might underlie the behavioral and social cognition difficulties previously reported in the preterm population.

The effects of cognitive behavioral therapy on the whole brain structural connectome in unmedicated patients with obsessive-compulsive disorder

Cognitive behavioral therapy (CBT) is considered a first-line treatment for patients with obsessive-compulsive disorder (OCD), and it possesses advantages over pharmacological treatments in stronger tolerance to distress, lower rates of drop out and relapse, and no physical “side-effects”. Previous studies have reported CBT-related alterations in focal brain regions and connections. However, the effects of CBT on whole-brain structural networks have not yet been elucidated. Here, we collected diffusion MRI data from 34 unmedicated OCD patients before and after 12 weeks of CBT. Fifty healthy controls (HCs) were also scanned twice at matched intervals. We constructed individual brain white matter connectome and performed a graph-theoretical network analysis to investigate the effects of CBT on whole-brain structural topology. We observed significant group-by-time interactions on the global network clustering coefficient and the nodal clustering of the left lingual gyrus, the left middle temporal gyrus, the left precuneus, and the left fusiform gyrus of 26 CBT responders in OCD patients. Further analysis revealed that these CBT responders showed prominently higher global and nodal clustering compared to HCs at baseline and reduced to normal levels after CBT. Such significant changes in the nodal clustering of the left lingual gyrus were also found in 8 CBT non-responders. The pre-to-post decreases in nodal clustering of the left lingual gyrus and the left fusiform gyrus positively correlated with the improvements in obsessive-compulsive symptoms in the CBT-responding patients. These findings indicated that the network segregation of the whole-brain white matter network in OCD patients was abnormally higher and might recover to normal after CBT, which provides mechanistic insights into the CBT response in OCD and potential imaging biomarkers for clinical practice.

Whole-brain structural covariance network abnormality in first-episode and drug-naïve major depressive disorder

There has been a growing interest in the abnormality of networks across the brain in major depressive disorder (MDD). We aimed to investigate the structural covariance networks in patients with first-episode and drug-naïve MDD using structural imaging. A total of 77 patients with first-episode and drug-naïve MDD and 79 healthy subjects (HS) were recruited, from whom high-resolution T1-weighted images were analysed. Incident component analysis was used to calculate the brain networks based on grey matter volume covariance. There were significant differences in salience network, medial temporal lobe network, default mode network and central executive network between MDD and HS (p < 0.05). Further, the disturbance of medial temporal lobe network was significantly correlated with the severity of depressive symptoms (p < 0.05). In conclusion, we found a novel abnormality in the brain network in the medial temporal lobe primarily involving the hippocampus and parahippocampal gyrus in patients with first-episode and treatment-naïve MDD.

The effect of network thresholding and weighting on structural brain networks in the UK Biobank

Whole-brain structural networks can be constructed using diffusion MRI and probabilistic tractography. However, measurement noise and the probabilistic nature of the tracking procedure result in an unknown proportion of spurious white matter connections. Faithful disentanglement of spurious and genuine connections is hindered by a lack of comprehensive anatomical information at the network-level. Therefore, network thresholding methods are widely used to remove ostensibly false connections, but it is not yet clear how different thresholding strategies affect basic network properties and their associations with meaningful demographic variables, such as age. In a sample of 3153 generally healthy volunteers from the UK Biobank Imaging Study (aged 44–77 years), we constructed whole-brain structural networks and applied two principled network thresholding approaches (consistency and proportional thresholding). These were applied over a broad range of threshold levels across six alternative network weightings (streamline count, fractional anisotropy, mean diffusivity and three novel weightings from neurite orientation dispersion and density imaging) and for four common network measures (mean edge weight, characteristic path length, network efficiency and network clustering coefficient). We compared network measures against age associations and found that: 1) measures derived from unthresholded matrices yielded the weakest age-associations (0.033 ​≤ ​|β| ​≤ ​0.409); and 2) the most commonly-used level of proportional-thresholding from the literature (retaining 68.7% of all possible connections) yielded significantly weaker age-associations (0.070 ​≤ ​|β| ​≤ ​0.406) than the consistency-based approach which retained only 30% of connections (0.140 ​≤ ​|β| ​≤ ​0.409). However, we determined that the stringency of the threshold was a stronger determinant of the network-age association than the choice of threshold method and the two thresholding approaches identified a highly overlapping set of connections (ICC ​= ​0.84), when matched at 70% network sparsity. Generally, more stringent thresholding resulted in more age-sensitive network measures in five of the six network weightings, except at the highest levels of sparsity (>90%), where crucial connections were then removed. At two commonly-used threshold levels, the age-associations of the connections that were discarded (mean β ​≤ ​|0.068|) were significantly smaller in magnitude than the corresponding age-associations of the connections that were retained (mean β ​≤ ​|0.219|, p ​< ​0.001, uncorrected). Given histological evidence of widespread degeneration of structural brain connectivity with increasing age, these results indicate that stringent thresholding methods may be most accurate in identifying true white matter connections.

Reduced segregation and integration of structural brain network associated with sympathetic and dorsal penile nerve activity in anejaculation patients: a graph-based connectome study.

Recent neuroimaging studies have indicated that some brain areas are involved in the sexual behavior process. Pre-mature ejaculation patients exhibit altered brain activation and abnormal cortical structures. However, there has been no research evaluating the topological organization of structural brain network in anejaculation (AE). We employed diffusion tensor imaging data and graph theory to examine the whole-brain structural networks among 16 AE patients and 23 healthy controls. In addition, the results of sexual function assessment were also obtained from each patient for symptom assessment. Moreover, the relationships between these clinical features and the altered topological characteristics of AE patients were also explored. Decreased clustering coefficient was found in the right amygdala, inferior temporal gyrus, and left pallidum of AE. AE also showed increased path length in the right post-central gyrus, supramarginal gyrus, putamen, pallidum and left heschl gyrus, temporal pole (superior temporal gyrus); however, these altered brain regions showed no significant differences after false discovery rate correction. Moreover, the path length between subcortical and frontal regions was increased in AE. In addition, negative correlations were found between the altered nodal parameters and the amplitudes of somatosensory evoked potentials of dorsal nerve, sympathetic skin response located in the penis. Together, our results suggest that AE was associated with disruptions in the topological organization of structural brain networks. The decreased clustering coefficient in temporal and subcortical regions and the increased path length between subcortical and frontal regions may contribute to AE. These findings provide new insights into the pathophysiological mechanisms of AE.

Abnormal structural brain network and hemisphere-specific changes\u2002in bulimia nervosa

Bulimia nervosa (BN) is characterized by episodic binge eating and purging behaviors. Disrupted neural processes of self-regulation, taste-rewarding, and body image has been associated with the pathogenesis of BN. However, the structural basis for these behavioral and functional deficits remains largely unknown. We employed diffusion tensor imaging and graph theory approaches (including the nodal properties and network-based statistics (NBS)) to characterize the whole-brain structural network of 48 BN and 44 healthy women. For nodal measures of strength, local efficiency, and betweenness centrality, BN patients displayed abnormal increases in multiple left-lateralized nodes within the mesocorticolimbic reward circuitry (including the orbitofrontal cortex, anterior cingulate, insular, medial temporal, and subcortical areas), lateral temporal-occipital cortex, and precuneus, while reduced global efficiency was observed in the right-lateralized nodes within the dorsolateral prefrontal cortex, mesocorticolimbic circuitry, somatosensory and visuospatial system. Several mesocorticolimbic nodes significantly correlated with BN symptoms. At a network level, we found increased left-lateralized connections primarily within the orbitofrontal cortex and its connections to mesocorticolimbic and lateral temporal-occipital areas, but reduced right-lateralized connections across the inferior frontal gyrus and insula, as well as their connections to the lateral temporal cortex. This study revealed BN-related changes in white-matter connections across the prefrontal control, mesocorticolimbic reward, somatosensory and visuospatial systems. The hemispheric-specific change could be an important aspect of the pathophysiology of BN. By characterizing whole-brain structural network changes of BN, our study provides novel evidence for understanding the behavioral and functional deficits of the disorder.

Brain structural connectivity network alterations in insomnia disorder reveal a central role of the right angular gyrus.

Insomnia Disorder (ID) is a prevalent and persistent condition, yet its neural substrate is not well understood. The cognitive, emotional, and behavioral characteristics of ID suggest that vulnerability involves distributed brain networks rather than a single brain area or connection. The present study utilized probabilistic diffusion tractography to compare the whole-brain structural connectivity networks of people with ID and those of matched controls without sleep complaints. Diffusion-weighted images and T1-weighed images were acquired in 51 people diagnosed with ID (21-69 years of age, 37 female) and 48 matched controls without sleep complaints (22-70 years of age, 31 female). Probabilistic tractography was performed to construct the whole-brain structural connectivity network of each participant. Case-control differences in connectivity strength and network efficiency were evaluated with permutation tests. People with ID showed structural hyperconnectivity within a subnetwork that spread over frontal, parietal, temporal, and subcortical regions and was anchored at the right angular gyrus. The result was robust across different edge-weighting strategies. Moreover, converging support was given by the finding of heightened right angular gyrus nodal efficiency (harmonic centrality) across varying graph density in people with ID. Follow-up correlation analyses revealed that subnetwork connectivity was associated with self-reported reactive hyperarousal. The findings demonstrate that the right angular gyrus is a hub of enhanced structural connectivity in ID. Hyperconnectivity within the identified subnetwork may contribute to increased reactivity to stimuli and may signify vulnerability to ID.